| | --- |
| | license: cc-by-4.0 |
| | language: |
| | - eu |
| | pretty_name: Maider Dataset |
| | size_categories: |
| | - 10k<n<100k |
| | task_categories: |
| | - text-to-speech |
| | - automatic-speech-recognition |
| | tags: |
| | - audio |
| | - TTS |
| | - Basque |
| | - Aholab |
| | - Ilenia |
| | - synthetic |
| | - common-voice |
| | base_model: |
| | - itzune/maider-tts |
| | --- |
| | |
| | # Maider Dataset (Synthetic) |
| |
|
| | This is a large-scale **synthetic speech corpus** designed for training and fine-tuning Basque Text-to-Speech (TTS) models. It consists of **99,996 audio files** synthesized from the "Maider" voice model. |
| |
|
| | This dataset was generated by **Itzune** and serves as the primary source for training the [itzune/maider-tts (Piper version)](https://huggingface.co/itzune/maider-tts) model. |
| |
|
| | ## Dataset Structure |
| |
|
| | Due to the large volume of data (approx. 100,000 files), the dataset is organized in the **WebDataset** format. The audio files are bundled into `.tar` shards to optimize storage, I/O performance, and streaming. |
| |
|
| | ### Files |
| | - **data/**: Directory containing the `.tar` shards. |
| | - **metadata.csv**: The main metadata file using `|` as a delimiter: |
| | - `file_name`: The name of the audio file (e.g., `audio_1.wav`). |
| | - `transcription`: The corresponding Basque text. |
| |
|
| | ## Technical Specifications |
| |
|
| | - **Audio Format:** WAV (PCM) |
| | - **Sample Rate:** 22050 Hz |
| | - **Language:** Basque (eu) |
| | - **Voice Profile:** Maider (Female) |
| | - **Text Source:** [Mozilla Common Voice - Basque Sentence Collection](https://datacollective.mozillafoundation.org/datasets/cmj8u3p2v007tnxxbk5ng5qvh) |
| | - **Generation Method:** Synthesized using VITS-based architecture. |
| |
|
| | ## Usage |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | dataset = load_dataset("itzune/maider-dataset", streaming=True) |
| | sample = next(iter(dataset["train"])) |
| | print(f"Text: {sample['transcription']}") |
| | ``` |
| |
|
| | ## Credits and Licensing |
| | ### Source and Methodology |
| |
|
| | This is a synthetic dataset generated by Itzune. The synthesis process involved: |
| |
|
| | - **Text Acquisition**: Sentences were sourced from the Mozilla Common Voice project (Basque sentence collection). |
| |
|
| | - **Audio Synthesis**: The audio was produced using the aHoTTS synthesis tools and the pre-trained Maider (VITS) model developed by HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory. |
| |
|
| | ### Acknowledgments |
| |
|
| | Mozilla Common Voice: For providing the community-driven sentence collection. |
| | |
| | HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory: For the underlying synthesis technology and the Maider voice model. |
| | |
| | Project ILENIA: The original Maider voice resource was developed with funding from Project ILENIA. |
| | |
| | ### License |
| |
|
| | Dataset Content (Audio & Text): Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). |
| | |
| | Original Tools/Code: The aHoTTS tools used to generate this data are licensed under the Apache License 2.0. |
| | |
| | ## Citation |
| | If you use this dataset, please cite the original work from HiTZ/Aholab: |
| | > García, V., Hernáez, I., & Navas, E. (2022). Evaluation of Tacotron Based Synthesizers for Spanish and Basque. Applied Sciences, 12(3), 1686. https://doi.org/10.3390/app12031686 |
| |
|
